Anurag K S V

Quantum Analyst (Founding Team), Qclairvoyance Quantum Labs, India.

Hi, thanks for stopping by.

I work on quantum computing, mainly at the intersection of computational chemistry and real-world applications like drug discovery. Most of my work involves building hybrid quantum–classical workflows and running them on actual hardware to understand what holds up beyond theory.

At Qclairvoyance, I develop quantum algorithms and software systems for molecular simulation, integrating them with classical methods and HPC infrastructure. This includes working with platforms like IBM and IQM, benchmarking performance, and translating these systems into workflows that can be used in practice.

My background spans both experimental and computational work — from quantum communication and optics experiments to GPU-accelerated simulation and scalable software systems. I tend to approach problems hands-on, whether that’s prototyping new ideas, optimizing performance, or building end-to-end systems.

More broadly, I’m interested in how quantum computing moves from research into practical use. Outside of work, I spend time playing basketball, working out, and writing.

news

Jul 23, 2026	Shared our preprint An Analytically Trained Variational Surrogate for Quantum Phase Estimation on NISQ Hardware on arXiv, for recovering the ground state energy of molecules.
Jul 22, 2026	Shared our preprint Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework on arXiv, where we make QSCI more efficient using RBM and integrate with DMET to simulate a protein-ligand complex.
Apr 22, 2026	Our work on Resource Estimation for VQE on Small Molecules: Impact of Fermion Mappings and Hamiltonian Reductions was published in the Journal of Computational Chemistry. An accepted version is available on arXiv.
Apr 02, 2026	Shared our preprint Towards Chemically Accurate and Scalable Quantum Simulations on IQM Quantum Hardware: A Quantum-HPC Hybrid Approach on arXiv, one of our more extensive experimental studies so far.
Mar 29, 2026	Our work on Engineering a phase-noise-based quantum random number generator for real-time secure applications: design, validation, and scalability was published in Proc. SPIE (OWT 2025).